output
20172025
most citedFractional derivative models for atmospheric dispersion of pollutants

72 citations

5 papers

cs.LG202320 cited

Predictive Maintenance Model Based on Anomaly Detection in Induction Motors: A Machine Learning Approach Using Real-Time IoT Data

Sergio F. Chevtchenko, Monalisa C. M. dos Santos, Diego M. Vieira +5

With the support of Internet of Things (IoT) devices, it is possible to acquire data from degradation phenomena and design data-driven models to perform anomaly detection in indust…

cs.LG202218 cited

Machine learning models and facial regions videos for estimating heart rate: a review on Patents, Datasets and Literature

Tiago Palma Pagano, Lucas Lemos Ortega, Victor Rocha Santos +6

Estimating heart rate is important for monitoring users in various situations. Estimates based on facial videos are increasingly being researched because it makes it possible to mo…

hep-ph20204 cited

Analytical representation for amplitudes and differential cross section of pp elastic scattering at 13 TeV

E. Ferreira, A. K. Kohara, T. Kodama

With analytical representation for the pp scattering amplitudes introduced and tested at lower energies, a description of high precision is given of the data at =…

cs.AI201960 cited

Multiobjective Coverage Path Planning: Enabling Automated Inspection of Complex, Real-World Structures

Kai Olav Ellefsen, Herman A. Lepikson, Jan C. Albiez

An important open problem in robotic planning is the autonomous generation of 3D inspection paths -- that is, planning the best path to move a robot along in order to inspect a tar…

physics.ao-ph201772 cited

Fractional derivative models for atmospheric dispersion of pollutants

A. G. O. Goulart, M. J. Lazo, J. M. S. Suarez +1

In the present work, we investigate the potential of fractional derivatives to model atmospheric dispersion of pollutants. We propose simple fractional differential equation models…